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dc.contributor.authorLi, Yung-Mingen_US
dc.contributor.authorLai, Cheng-Yangen_US
dc.contributor.authorChen, Ching-Wenen_US
dc.date.accessioned2014-12-08T15:20:33Z-
dc.date.available2014-12-08T15:20:33Z-
dc.date.issued2011-12-01en_US
dc.identifier.issn0020-0255en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ins.2011.07.023en_US
dc.identifier.urihttp://hdl.handle.net/11536/14642-
dc.description.abstractDiscovering influential bloggers will not only allow us to understand better the social activities taking place in the blogosphere, but will also provide unique opportunities for sales and advertising. In this paper, we develop an MIV (marketing influential value) model to evaluate the influential strength and identify the influential bloggers in the blogosphere. We analyze three dimensions of blog characteristics (network-based, content-based, and activeness-based factors) and utilize an artificial neural network (ANN) to discover potential bloggers. Based on peer and official evaluations, the experimental results show that the proposed framework outperforms two social-network-based methods (out-degree and betweenness centrality algorithms) and two content-based mechanisms (review rating and popular author approaches). The proposed framework can be effectively applied to support marketers or advertisers in promoting their products or services. (C) 2011 Elsevier Inc. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectInfluential modelen_US
dc.subjectViral marketingen_US
dc.subjectSocial networksen_US
dc.subjectBlogosphereen_US
dc.subjectArtificial neural networken_US
dc.titleDiscovering influencers for marketing in the blogosphereen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ins.2011.07.023en_US
dc.identifier.journalINFORMATION SCIENCESen_US
dc.citation.volume181en_US
dc.citation.issue23en_US
dc.citation.spage5143en_US
dc.citation.epage5157en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000295760600002-
dc.citation.woscount9-
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